{"id":"W3126015569","doi":"","title":"Measuring Cross Country Monetary Policy Uncertainty","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monetary policy; Work (physics); Index (typography); Economics; Quantitative easing; Macroeconomics; Central bank; Computer science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002033892,0.0004644919,0.0005500113,0.003446713,0.0003569351,0.002155424,0.0002553239,0.0005963959,0.001847249],"category_scores_gemma":[0.01602087,0.0001979395,0.0002626637,0.005385814,0.0004203644,0.001926628,0.001072586,0.0006780493,0.0002683367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008784487,"about_ca_system_score_gemma":0.0003057806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00604404,"about_ca_topic_score_gemma":0.003442646,"domain_scores_codex":[0.9989251,0.0002897166,0.0001006797,0.0002682652,0.0003335461,0.00008268768],"domain_scores_gemma":[0.9900996,0.005068908,0.002900708,0.0004790384,0.001189317,0.0002624544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009696786,0.000220083,0.7129294,0.0004111739,0.001284408,0.000493897,0.002699837,0.1255651,0.003356799,0.03526581,0.005840422,0.1109634],"study_design_scores_gemma":[0.00006009761,0.000415325,0.723524,0.0002905586,0.0006699641,0.0005005955,0.003833979,0.1860756,0.01112928,0.04514899,0.02803675,0.0003148142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9442818,0.002056925,0.02891735,0.0004187031,0.000135131,0.00004528112,0.005255208,0.0001196385,0.01876992],"genre_scores_gemma":[0.9939787,0.0005497698,0.002802418,0.00004227149,0.00008558463,0.00002675553,0.002015291,0.00001482083,0.0004844493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00604404,"threshold_uncertainty_score":0.01201773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1099439125120539,"score_gpt":0.314975601093017,"score_spread":0.2050316885809632,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}